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Record W6948633573 · doi:10.5061/dryad.9ghx3ffg0

Overexpression of an ALS-associated FUS mutation in C. elegans disrupts NMJ morphology and leads to defective neuromuscular transmission

2020· dataset· en· W6948633573 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2020
Typedataset
Languageen
Field
Topic
Canadian institutionsLunenfeld-Tanenbaum Research Institute
Fundersnot available
KeywordsAmyotrophic lateral sclerosisNeurotransmissionNeuromuscular junctionMutationEctopic expressionMutantMotor neuronPopulationNeuromuscular transmission

Abstract

fetched live from OpenAlex

The amyotrophic lateral sclerosis (ALS) neurodegenerative disorder has been associated with multiple genetic lesions, including mutations in the gene for FUS (Fused in Sarcoma), a nuclear-localized RNA/DNA-binding protein. Neuronal expression of the pathological form of FUS proteins in C. elegans results in mislocalization and aggregation of FUS in the cytoplasm, and leads to impairment of motility. However, the mechanisms by which the mutant FUS disrupts neuronal health and function remain unclear. Here we investigated the impact of ALS-associated FUS on motor neuron health using correlative light and electron microscopy, electron tomography, and electrophysiology. We show that ectopic expression of wild-type or ALS-associated human FUS impairs synaptic vesicle docking at neuromuscular junctions. ALS-associated FUS led to the emergence of a population of large, electron-dense, and filament-filled endosomes. Electrophysiological recording revealed reduced transmission from motor neurons to muscles. Together, these results suggest a pathological effect of ALS-causing FUS at synaptic structure and function organization.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.024
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0190.012

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.333
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2020
Admission routes1
Has abstractyes

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